Inside France's Plan to Become a Global Hub for Artificial Intelligence

Under the leadership of startup champion President Emmanuel Macron, France has announced an initiative aimed at turning the country into a world-leading AI hub.

The strategy will see the investment of $1.85bn (€1.5bn) into AI projects, create a national AI research program, make it easier for entrepreneurs to create startups based on their research, and encourage data sharing between French administrations.

The new funding joins an existing $11.2 billion (€10 billion) public fund managed by Bpifrance, which supports AI projects as a priority, as well as recent investment in the country from leading private companies. Commitments made in the past 12 months include new Paris labs for Google DeepMind and Samsung, an expansion of Fujitsu’s existing Paris research centre and announcements from Google and Facebook earlier this year of increased investments in their Paris-based AI labs.

The new government support follows the publication of a government-funded AI For Humanity report, in which academics and politicians looked at how to develop the country’s AI economy. The document raised concerns about AI research and policy being increasingly driven by the U.S. and China, considered strategies for boosting the development of AI in France, and looked at the social impact of the tech, including its potential to displace the human workforce.

“[Artificial intelligence] is a technological, economical, social and obviously ethical revolution,” said Macron in a late March speech delivered from underneath a banner reading ‘AI for Humanity’. “This revolution won’t happen in 50 or 60 years, it’s happening right now. There are new opportunities and we can choose to follow some innovations or not.”

The President addressed the upcoming European privacy standard, known as GDPR, which places heavy restrictions on the collection and use of private data, and focussed on the moral impact of artificial intelligence – arguing that the AI developers must be sure that there’s no bias in training data sets.